Computational studies to explore inhibitors against the cyclin-dependent kinase 12/13 enzyme: an <i>insilco</i> pharmacophore modeling, molecular docking and dynamics approach

Cancer is enlisted among the deadliest disease all over the world. The cyclin-dependent kinases 12 and 13 have been identified as cell cycle regulators. They conduct transcription and co-transcriptional processes by phosphorylating the C-terminal of RNA polymerase-II. Inhibition of CDK12 and 13 selectively presents a novel strategy to treat triple-negative breast cancer, but dual inhibitors are still lacking. Here, we report the screening of the natural product compound class against the dual CDK12/13 enzyme by employing various in silico methods. Complexes of CDK12 enzymes are used to form common feature pharmacophore models, whereas we perform receptor-based pharmacophore modelling on CDK13 enzyme owing to the availability of a single PDB. On conducting screening over the representative pharmacophores, the common drug-like screened natural products were shortlisted for conducting molecular docking studies. After molecular docking calculations, the candidates that showed crucial interaction with CDK12 and CDK13 enzymes were shortlisted for simulation studies. Five common docked candidates were selected for molecular dynamics simulations and free energy calculations. Based on the cut-off criteria of free energy calculations, one common hit was selected as the dual CDK12/13 inhibitor. The outcome concluded that the hit with ID CNP0386383 possesses drug-like properties, displays crucial interaction in the binding pocket, and shows stable dynamic behaviour and higher binding energy than the experimentally reported inhibitor of both CDK12 and CDK13 enzymes. Communicated by Ramaswamy H. Sarma